Data Processing Cycle and Database for Accounting

When you observe a chef making a dish, you can clearly see that he

has arranged a variety of components systematically in front of him.

The perfect arrangement of these components is required to cancel the

confusion and prepare the dish efficiently. Same is the case with

accountancy. Data processing is the carrying out systematic operations

on data, especially by a computer, to retrieve, store, transform, or

classify information.

Data Processing Cycle

To begin with, we know that information is the final product of data.

The quality of the final information obtained is directly related to data

used in the first place. Keeping in mind the end goal of database

design, let us comprehend the data processing cycle used in

accounting. Data Processing includes the procedure of gathering,

arranging, relating, translating and registering the data in such a way

as to give reasonable and valuable information in the decision making

the process of the administration.

Few crucial steps associated with the data processing cycle are data

occupying, inputting, computing and generating information

accessible to the user. As a result, Data Processing cycle when seen

with regards to accounting needs multiple guidelines which are

mentioned below;

Source Documents

Usually, the initial step is to occupy accounting data from the

transaction(s) to make a report, known as a voucher (as expressed

before), that proves and reports an accounting exchange.

Input of Data

The accounting data comprised in vouchers is to be fed in PC’s

memory device. This is accomplished by utilizing a pre-planned Data

Entry Form. This form is planned in a way that it is like a physical

voucher document. Data entry form is made utilizing software and it is

designed to show up on the PC screen so that the data is entered.

Data storage

An appropriate data storage structure is needed to accommodate a

clear data record as demonstrated as follows;

Code Name Type

The above clear record that is utilized for accumulating the input of

data regarding code of account, the name of the account and the

category type to which it belongs is demonstrated below;

Code Name Type

B1212 Capital Account 4

56654 Purchases Account 1

Speculatively, the category type 4 above points towards Liabilities and

the category type 1 point towards Expenses. The Data storage

structures (additionally called data tables) are made as a segment of

structuring database for accounting.

Manipulation of Data

The collected information is controlled for a fundamental change to

create final reports. Such changed information might be collected

independently and in this way utilized for creating final reports. On

the contrary, the changed information can be specifically exhibited in

the name of a report.

Output of Data

The accounting documents, for example, a ledger, a trial balance, and

so on are acquired in a pre-outlined format by getting to the changed

information. Since you learned about the manner in which data

content is collected in an organized way, we will examine how the

data structures are composed in consonance with the data content that

rises up out of accounting exchanges.

(Source: DataIreland)

Database for Accounting

An organization is built up to take over one or numerous ventures.

Normally in a situation with a single administration. Such cases of

organizations are banks, medical centers, producers, and so forth.

Every one of these organizations has diverse functions yet at the same

time, there are a few essentials or regular functions performed by

every one of the organization. One regular function of the organization

is ‘accounting’.

Computerized and PC based AIS need a firm data structure for

reserving the information of the transaction. Above all, the databases

are utilized for reserving accounting data. The guidelines of the

planning database (for accounting) starts with a reality (also

accounting reality) that is communicated using components of a

conceptual data model.

● Reality: It takes into consideration some part of real-world

circumstances, for which database is to be designed. In

particular, with regards to accounting, it is the accounting

reality that will be defined with the utmost precision.

● ER Design: This is a formal blueprint, with a pictures format,

in which Entity-Relationship (ER) Model ideas are utilized for

the portrayal of reality.

● Relational Data Model: It is authentic data model through

which ER configuration is changed between related data tables

alongside the limitation in the form of rules that are indicated

to guarantee the consistency and respectability of accumulated

data.

● Standardization: Specifically, this is the procedure of refining a

database outline (that comprises interrelated data tables)

through which the likelihood of copy or repeated information

things are eliminated or disposed of.

● Refinement: Consequently, this is the result of the procedure of

standardization as said above. The final database configuration

is reached after the procedure of standardization is finished.

Solved Question for You

Q: How is the data manipulated?

Ans: The collected information is controlled for a fundamental change

to create final reports. Such changed information might be collected

independently and in this way utilized for creating final reports. On

the contrary, the changed information can be specifically exhibited in

the name of a report.

Designing Relational Database Schema and Interaction with Databases

A database is a collection of interrelated data files or structures. It is

designed to meet the various information needs of the organization

and is integrated and shared. Thus, a relational database schema is an

arrangement of relation states in such a manner that every relational

database state fulfills the integrity constraints set on the relational

database schema. Let us now discuss RDBMS in detail.

RDBMS: Designing Relational Database Schema

The guidelines or rules to design the relational database schema

provide a step-by-step procedure. This procedure converts the ER

design into a Relational Data model design in order to form the

desired database. Following are the steps to convert the ER design into

a Relational Data model design:

1. Creation of relation for each substantial entity

For every strong or substantial entity type in ER schema, we need to

create a separate relation including all the simple characteristics of

that entity. This entity shall have a primary key.

We can choose either a key characteristic of the entity or a set of

simple characteristics that will unambiguously identify this entity as

the primary key of this relation.

For example, delivery vehicles entity is strong as it finds its primary

key in Registration No. which is its unique characteristic.

Learn more about Relational Database and Schema here in detail.

2. Creation of a separate relation for each weak entity type

Each weak entity needs to have an owner entity. It also has an

identifying relationship by which we can identify this weak entity

type. We need to create a separate relation for every weak entity

including its characteristics.

A combination of its unique characteristics and a primary key

characteristic of such owner relation form its primary key. Further, we

include the primary key of the owner entity as the foreign key in this

relation key of owner entity and the partial key of the weak entity.

3. Identification of entity types participating in binary 1: N relationship type

We need to identify first the relation on n-side of relationship and

secondly on 1-side of this relationship. We include the primary key of

the second relation in the first relation as its foreign key.

For example, a single employee can pass a number of purchase

vouchers. It indicates that Purchase Vouchers entity participates in

AuthBy relationship on n-side whereas Employees entity is

participating in the same relationship on 1-side.

4. Identification of entity types participating in binary M: N relationship type

We need to create a new relation for each binary M: N relationship

type to represent this relationship. This relation needs to include as

foreign keys, the primary keys of the relations representing the

participating entity types.

Interaction with Databases

The Structured Query Language or SQL makes it easy for the user to

interact with the database. It is a comprehensive database language

and contains statements for data definition, query, and update.

SQL also facilitates the migration of the users from one database

application to another database application. Data Query Language

(DQL) is a subset of SQL and is mostly in use to get the answer of

most of the basic queries. The basic set of queries consists of:

1. SELECT: We use this clause to specify the data or information

that we require to answer the query.

2. FROM: We use this clause to specify the source of data for

answering the query which can be a data table, an existing

query or a combination of both.

3. WHERE: We use this clause to specify the conditions that we

apply to narrow down the choice of data in order to extract the

data information that is desirable in the SELECT clause.

Solved Example For You

Explain the queries that we need to consider while using the database

design given in Model-I and Model-II.

Ans.

We generally use MS ACCESS implementation to give the solution to

these queries. The queries and their solutions are as follows:

1. To recover all columns of data from a table, subject to a specific condition

In order to project all the characteristic values of the selected tuples,

we need to specify an asterisk sign (*). It stands for all the

characteristics. For example, the query is to recover all the columns of

purchase vouchers passed by an employee whose employee id is

B002.

Solution:

SELECT *

FROM Purchase Vouchers

WHERE AuthBy= “B002”;

3. To recover selected columns of data from a table, subject to a

specific condition

For example, the query is to recover purchase vouchers with voucher

number, voucher date and authorized by columns where the vouchers

are dated 6 April 2018.

Solution:

SELECT Vno, Vdate, AuthBy

FROM Purchase Vouchers

WHERE Vdate = #4/6/2018#:

3. WHERE clause is unspecified

The absence of the WHERE clause indicates that we need to select the

tuples from a relation without applying any condition. For example,

the query is to find out the list of all the accounts that have been

credited under Model I.

Solution:

SELECT DISTINCT Credit As Code

FROM vouchers:

4. Unique characteristic names and renaming (aliasing):

The SQL allows the use of the same name for two or more

characteristics as long as such characteristics are in different relations.

Therefore, in a case where the use of a common characteristic with a

particular name across the relations persists, it is essential to qualify

the characteristic name with relation name in which it exists.

For example, the query is to recover a list of accounts and the amounts

credited due to bank receipts. The Bank A/c Code is 420.

Solution:

Model I

SELECT Narration, Credit As Code, Amount

FROM Vouchers

WHERE Debit LIKE “420*”;

Entity Relationship (ER) Model

The entity-relationship (ER) data model is created out of the activity

of utilizing commercially accessible DBMS to model application

database. Prior, business systems depended on the various leveled and

network approach. The entity-relationship model is a speculation of

these models. It contains an ER Diagram which is crucial for the

overall ease and speculation on the ER Model.

Browse more Topics Under Structuring Database For Accounting

● Data Processing Cycle and Database for Accounting

● Designing Relational Database Schema and Interaction with

Databases

● Entity Relationship (ER) Model

● Relational Databases and Schemas

● Illustration of Accounting Database

ER Model and ER Diagram

ER Model permits the portrayal of explicit limitations and

relationships. This model of the database comprises of entities,

attributes, identifiers and relationship which are a way to express a

reality for which database is to be made. The database structure,

utilizing the ER Model, is typically demonstrated pictorially by the

means of entity-relationship, i.e. ER diagram.

The entities and the relationships between them are demonstrated by

using the ER symbols (part of ER diagram) to show various kinds of

entities, attributes, identifiers, and relationships. The symbols, which

are utilized for the purpose of an ER diagram, are institutionalized and

are as per the following

ER Diagram

Entity Type as Rectangular Box

Weak entity Type as double lined Rectangular Box

Relationship Type as diamond-shaped Box

Identifying relationship Type as double

lined diamond shaped Box

Attribute names enclosed in ovals and

attached to their entity type by straight lines.

Key attribute names enclosed in ovals and

attached to their entity type by straight lines.

Multi-valued attributes by double ovals

Derived attributes by dashed line Ovals

Total participation of E2 in R

Cardinality Ratio 1 : N

for E1 : E2 in R

What is Relational Database Schema??

Learn here.

Entity

Entities are the fundamental units utilized in modeling classes of

concrete or conceptual objects. An entity is an object that is important

to a business. Objects of the same kinds are described by a similar

arrangement of attributes or properties. As such, we can state that the

autonomous presence of a thing is known as an entity.

Most importantly, two objects are commonly recognizable and this

fact is demonstrated in the entity set by giving them exceptional

identifiers. In this way, an entity implies an object having a physical

presence (e.g., individual, office, furniture, and so forth.) or

conceptual presence (e.g., organization).

We have examined the accounting reality above. It has five entities –

accounts, vouchers, employees, account types, and proof or support

reports. In other words, the accounting information is collected

through these entities.

Learn about Data processing cycle and

Database of Accounting here.

Attributes and Identifiers

The properties that portray or further depict an element are called its

traits. Each question must be independently recognized as a substance.

Recognizing and ordering the items into an element can be

troublesome in light of the fact that a question can have a place with

various substances in the meantime or at least two elements might be

comparative.

In such cases, they should be additionally depicted so every element is

recognized and independently distinguished. Substances are

recognized and displayed utilizing their qualities or properties.

An affiliation exists between various qualities of an element. A

relationship between two properties demonstrates that the estimations

of the related characteristics are associated. This correspondence

between qualities of a substance is a property of the data that is

utilized in displaying the question. Therefore, we recognize the

affiliations that exist among the traits of a substance, called a

relationship.

Think about the representatives of the firm. The firm keeps up certain

data, for example, name, date of birth, address, assignment, name, and

relationship of wards, about every representative. In any case, this data

can coordinate with the data of some other representative. Along these

lines, one of a kind data like worker distinguishing proof number or

code is fundamental about every one of them by which they can be

recognized. This one of a kind number is known as an identifier.

Entity Types and Entity Sets

(i) Composite versus Basic (or atomic) Attributes

The composite attributes can be diversified into sub-parts to speak to

demonstrate some more basic attributes with free implications. The

straightforward traits can’t be additionally sub-partitioned. For

instance, Name of a man that is regularly subdivided into First Name,

Middle Name, and Last Name is a composite trait. The tallness of a

man is a straightforward quality as it is without further sub-division.

(ii) Single-esteemed versus Multi-esteemed Attributes

A trait with a solitary esteem for an element is single-esteemed rather

than those which various qualities. For instance, the stature of a man is

single-esteemed quality while the capabilities of that individual area

multi-esteemed property.

(iii) Stored versus Determined Attributes

At least two properties might be connected in such a route, to the point

that at least one winds up essential while alternate moves toward

becoming reliant on that essential property. For instance, the date of

birth of a man is a putaway property while the age of that individual is

inferred quality.

(iv) Null Values

The absence of an information thing is spoken to by an extraordinary

esteem called the invalid esteem. There are three circumstances which

may require the utilization of invalid qualities

● When a specific ascribe does not have any significant bearing

to a substance;

● Value of a quality is obscure, in spite of the fact that it exists;

● Unknown since it doesn’t exist.

(v) Complex Attributes

The composite and multi-esteemed qualities might be settled (or

assembled) to constitute complex ones. The enclosure () is utilized for

demonstrating a gathering of segments of composite qualities. The

props {} are utilized for demonstrating the multi-esteemed qualities.

Relationships

A connection among elements is known as a relationship. The

relationship set is utilized in the information displaying to speak to a

relationship between element sets. This affiliation may have certain

properties spoken to by the traits of the relationship set. A gathering of

connections of a similar kind is known as a relationship set.

A relationship that includes N substances is called N-ary relationship.

A relationship is a paired relationship if the number of entities sets

engaged with the relationship is two. Enrolment is a case of a parallel

relationship including two particular substance sets like between the

understudy and course.

The examination is a case of a twofold relationship which

demonstrates the connection between an understudy and move

number. Similarly, processing is a case of a ternary relationship which

speaks to the relationship including an understudy utilizing a specific

figuring framework to do the calculations for a given course.

Similarly, at whatever point a characteristic charge or credit of one

element compose voucher alludes to another element compose

Accounts, there exists a connection between these substances as

vouchers and Accounts. Vouchers and records are connected in two

different ways, Vouchers contain the charge and furthermore the

credit accounts. A relationship compose characterizes the relationship

of substance compose and a relationship occasion is a relationship of

element examples.

The sections of a connection hold the estimation of the credits that we

wish to connect with every substance case, and each is marked with a

particular property name at the highest point of the segment. This

name, obviously, gives a remarkable reflection to the whole section or

to a specific estimation of a tuple in the connection.

Learn about Designing Relational Database here in detail.

Solved Question for You

Q: What is a weak entity?

Ans: A weak entity is one which does not have an identifier of its

own. A weak entity type is identified with respect to its relationship

because it cannot be identified without own owner entity. Let us

consider a voucher.

A voucher may be accompanied by a set of support documents, such

as bills, detail of expenses, issued by other parties to the transaction.

Such support documents are weak entity type which is used to keep

track of support documents attached to each voucher via N-

relationship.

Relational Databases and Schemas

A database is a collection of interrelated data files or structures. It is

designed to meet the various information needs of the organization.

Also, it is integrated and shared. Thus, a relational database schema is

an arrangement of relation states in such a manner that every relational

database state fulfills the integrity constraints set on a relational

database schema.

Relational Database and Schemas

As we know that a relational database schema is an arrangement of

integrity constraints. Thus, in the context of relational database

schema following points deserve a particular consideration:

1. A specific characteristic, that bears the same real-world

concept, may appear in more than one relationship with the

same or a different name. For example, in Employees relation,

Employee Id (EmpId) is represented in Vouchers as AuthBy

and PrepBy.

2. The specific real-world concept that appears more than once in

a relationship should be represented by different names. For

example, an employee is represented as subordinate or junior

by using EmpId and as a superior or senior by using SuperId, in

the employee’s relation.

3. The integrity constraints that are specified on database schema

shall apply to every database state of that schema.

Learn more about the Entity-Relationship Model here in detail.

Image Source: stackoverflow

Browse more Topics Under Structuring Database For Accounting

● Data Processing Cycle and Database for Accounting

● Designing Relational Database Schema and Interaction with

Databases

● Entity Relationship (ER) Model

● Relational Databases and Schemas

● Illustration of Accounting Database

Constraints and Database Schemas

Domain constraint, Key constraint, Entity integrity constraint, and

Referential integrity constraint are the four different constraints of the

relational databases. Let us now discuss them in detail.

1. Domain constraint: The value of each characteristic of a

relationship needs to be an indivisible value and we need to

draw it out of the possible values corresponding to its domain.

Thus, the value of a characteristic needs to adjust to the data

type corresponding to the domain.

2. Key constraints and Null values: Each data record that relates

to a tuple of a relation in a table needs to be distinct. Thus, this

implies that no two rows or tuples in relation or table can have

the same combination of values for their entire data item. Every

relation has a super key by default and depicts uniqueness

constraints. It is a combination of all the characteristics.

Sometimes a relation can have more than just one key. Each

such key is a candidate key. Out of these, we need to define

one of the keys as the Primary Key.

3. Entity integrity constraint: This constraint states that primary

key value cannot be null as it defines the individual tuple in a

relation. A null value indicates the failure to identify such

tuples and thus it means that they are duplicates.

4. Referential integrity constraint: It is specified to maintain the

consistency among the tuples of two or more relations.

Solved Example For You

Explain the operations and constraint violations?

Ans. Updates and retrieval are the two categories of operations on the

relational model. The basic types of updates are:

1. Insert: We use this operation in order to add a new tuple in a

relation. It is capable of violating any of the four constraints.

2. Delete: We perform this operation in order to remove or delete

a tuple in a relation. Under this operation, we can remove a

particular data record from a table. It can only violate the

referential integrity constraint.

3. Modify: This operation causes a change in the values of some

characteristic of existing tuples or accounting data tables.

Retrieval constraints do not cause a violation of integrity constraints.

Illustration of Accounting Database

A database is a shared collection of inter-related data tables which

meet the various informational needs of an organization. Thus, an

accounting database stores the accounting data. It is a collection of

accounting data which is inter-related to depict the various aspects of

the accounting information system.

Illustration of Accounting Database

Following is an example of Accounting Database for maintaining data

relating to the accounting transactions, source documents, accounts,

and employees.

Date Transactions Amount (₹)

2018

Apr. 01 Commenced business with cash 600000

Apr. 03 Deposited cash into bank 500000

Apr. 05 Purchased goods and paid by cheque no. 756431 120000

Apr. 07 Salary paid in advance by cheque no. 756432 10000

Apr. 09 Purchased goods for cash 60000

Image source: stackexchange

Employees

Emp_Id Fname Minit LName Address PhoneNo Super_Id

A001 Anil K Madhuri

B001 Akshay S Raveena A001

T001 Aamir K Juhi A001

T002 Salman K Nagma B001

Vouchers

Vno Debit Amount VDate Credit Narration AuthBy PrepBy

2018

01 731001 600000 Apr.

01 110001

Commenced business with cash

A001 B001

02 732001 500000 Apr.

03 731001

Deposited cash into bank A001 T001

03 811001 120000 Apr.

05 732001

Purchased goods and paid by cheque no. 756431

A001 B001

04 812002 10000 Apr.

07 732001

Salary paid in advance by cheque no. 756432

A001 B001

05 811001 60000 Apr.

09 731001

Purchased goods for cash A001 T001

Support

Vno Sno Name

02 1 Cash deposit receipt

03 1 Purchase invoice no….dated….

03 2 Delivery challan

04 1 Salary receipt for April 2018

05 1 Purchase invoice no….dated….

Learn more about the Relational Database and Schema here.

Accounts

Code Name Type

110001 Capital account 4

731001 Cash account 3

732001 Bank account 3

811001 Purchases 1

811003 Carriage inwards 1

812002 Salary 1

811001 Wages 1

Account Type

Cat_Id Category

1 Expenditure

2 Income

3 Assets

4 Liabilities

Solved Example for You

What is a modified version of the Accounting Database?

Ans. An effort to fit the Debit and Credit vouchers results in the

addition of a new column Sno to Vouchers table of accounting

database. This results in the data redundancy. ER Model is a

conceptual model. We need to transform it into a representational data

model so that we can form a database design for the implementation

and operation upon while using the DBMS.